With the development of Electronic Commerce (e-commerce), more and more users purchase items using e-commerce services. In general, an e-commerce website owns tens of millions or even hundreds of millions of items, and thus the users have to search the website to find desired items. A server associated with the website may perform searches based on keywords provided by the users, and return results corresponding to the keywords.
In response to a keyword, the server may produce a larger number of search results. Accordingly, the search results need to be sorted and/or ranked according to a certain order during presentation. The server may take comprehensive consideration into how to rank these search results. For example, search results may be ranked according to a correlation between the search results and a keyword, previous click-through rates, previous deals associated with the search results, and etc. For an e-commerce website, to improve the sales volume of a commodity, the server may also consider deal feasibilities (e.g., deal conversion rates and positive feedback rates of search results).
Currently, a server of an e-commerce website ranks search results based on the correlation and deal feasibility predictions that are generally obtained based on manual analysis on historical data, empirical determination of commodity characteristics and weights of the search results (i.e. a specific commodity), and/or calculations according to a certain formula. Commodity characteristics refer to factors that are capable of affecting the deal feasibility of the commodity (e.g., sale volumes, positive feedback rates, and deal conversion rates). Since determination of characteristics and weights by empirical setting is relatively random and subjective, errors often occur. The returned search results may differ significantly from what the users desired, or ranking of the search results may not satisfy the users. Because the server may only return a certain number of search results, the users may not receive their desired results. To obtain their desired results, the users may modify keywords and re-submit queries. This causes the server to have increased data transmission, which undoubtedly increases the burden on the server and occupies a lot of network resources or even leads to network congestion. Meanwhile, this also indicates that the search results returned by the server have a large amount of irrelevant data, and server resources and network resources are therefore wasted.